JP4849013B2 - Vehicle periphery monitoring device - Google Patents

Description

  The present invention relates to a vehicle periphery monitoring device.

  In recent years, driving support devices such as a collision reducing device, an inter-vehicle distance control device, and a following traveling device have been developed. In these driving support devices, it is important to constantly monitor the surroundings of the host vehicle and grasp the relative positional relationship between the host vehicle (for example, a vehicle traveling ahead) and the host vehicle and the rate of change over time. . The vehicle periphery monitoring device is a device that provides such information to the driving support device, and includes radar detection means such as a millimeter wave radar and image detection means such as a stereo camera in order to improve object detection accuracy. By using the radar detection means, the presence of an object can be detected accurately, and the distance between the host vehicle and the object can be detected with high accuracy. In addition, using the image data obtained by the image detection means, it is possible to accurately detect the edge of the object from the shade of the image, so the information about the edge (edge) is used to accurately determine the position of the object with respect to the host vehicle. Can be detected well. Therefore, the vehicle periphery monitoring device including these two detection means is configured to move the object relative to the host vehicle based on the distance information to the object obtained by the radar detection means and the position information of the object obtained by the image detection means. The direction and relative movement speed (hereinafter referred to as a relative movement vector) can be calculated with high accuracy.

As a conventional apparatus for detecting the relative positional relationship between the host vehicle and the surrounding object, for example, the following is available. In the collision determination apparatus described in Patent Literature 1, the vertical edge and the horizontal edge of an object existing in an image captured by the image detection unit are extracted, optical flows related to these edges are calculated, and based on the optical flow The possibility of collision with the object is determined. In the inter-vehicle distance estimation device described in Patent Document 2, the inter-vehicle distance between the host vehicle and the preceding vehicle detected by the radar and the edge interval of the preceding vehicle detected by the camera image are stored in association with each other. When the inter-vehicle distance becomes shorter than a predetermined value, the current inter-vehicle distance is estimated using the previous inter-vehicle distance, the edge interval, and the current edge interval. In the image recognition apparatus described in Patent Document 3, the height of an object and the height of a shadow are detected by analyzing an infrared image captured by one infrared camera, and the detected height and shadow of the object are detected. The ratio of the height of the object and the angle of the shadow with respect to the object are calculated, and the distance from the vehicle to the object is calculated based on the calculated ratio and angle.
JP 2006-99155 A JP 2002-96702 A JP 2005-92448 A

  However, when detecting the edge of an object using an image captured by the image detection means, the larger the angle formed between the direction of the edge viewed from the image detection means and the imaging center axis of the image detection means (that is, The closer the end of the object in the image is to the end of the image), the lower the position detection accuracy for that end. As a result, the position detection accuracy related to the object is lowered, which affects the calculation accuracy of the relative movement vector.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to improve the calculation accuracy of a relative movement vector of an object with respect to the host vehicle in a vehicle periphery monitoring device including image detection means.

  In order to solve the above-described problem, a vehicle periphery monitoring device according to the present invention is a vehicle periphery monitoring device that detects a relative movement direction and a relative movement speed of an object with respect to the host vehicle, and transmits a transmission wave to be reflected by the object. The left edge lateral position of the object based on the radar detection means for generating the distance information and lateral position information of the object with respect to the host vehicle by receiving the reflected wave, and the image and lateral position information obtained by imaging the object Image detecting means for generating information and right end lateral position information, and computing means for calculating the relative movement direction and relative movement speed of the object relative to the host vehicle based on the distance information, the left end lateral position information, and the right end lateral position information. And calculating means weights each of the left end lateral position information and the right end lateral position information to calculate a relative moving direction and a relative moving speed of the object with respect to the own vehicle, and When only the, characterized by greater than the far side of the weight of the positional information closer to the center of the image of the left lateral position information and the right end lateral position information.

  In the vehicle periphery monitoring device described above, the calculation means weights each of the left end lateral position information and the right end lateral position information to calculate the relative movement vector of the object with respect to the own vehicle, and at the time of weighting, the left end lateral position Among the information and right end lateral position information, the weight of the position information closer to the center of the image is made larger than that of the far side. The position information on the side close to the center of the image is relatively small in the angle formed by the direction of the end as viewed from the image detection means and the imaging center axis of the image detection means, so it is compared with the position information on the side far from the center. And high accuracy. Therefore, the relative movement vector of the object with respect to the host vehicle can be accurately calculated by increasing the weight of the position information on the side closer to the center of the image than on the far side.

  In the vehicle periphery monitoring apparatus described above, the calculation means weights each of the left end lateral position information and the right end lateral position information to calculate the relative movement vector of the object with respect to the own vehicle. The relative position of the object with respect to the host vehicle is calculated by adding the first value obtained by multiplying the weighting coefficient of the second position and the second value obtained by multiplying the right end lateral position information by the second weighting coefficient. Based on the position, the relative movement direction and the relative movement speed of the object with respect to the host vehicle are calculated, and when the left end is closer to the center of the image than the right end of the object, the first weighting coefficient is calculated from the second weighting coefficient. For example, when the right end is closer to the center of the image than the left end of the object, the second weighting coefficient is made larger than the first weighting coefficient.

  In addition, the vehicle periphery monitoring device may be configured such that when the lateral position of the object is within a predetermined range from the center line of the host vehicle, the vehicle periphery monitoring device does not perform weighting and the relative movement direction of the left end of the object with respect to the host vehicle Calculate the relative movement speed, the relative movement direction and the relative movement speed of the right end of the object with respect to the own vehicle, and calculate the relative movement direction and the relative movement speed of the object with respect to the own vehicle based on the relative movement direction and the relative movement speed. It may be characterized by.

  When the lateral position of the object is within a predetermined range from the center line of the host vehicle, both the left end and the right end of the object are close to the center of the image in the image, and both the left end lateral position information and the right end lateral position information are both It can be said that the accuracy of is high. Therefore, in such a case, the left end relative movement vector and the right end relative movement vector can be calculated with high accuracy, and the relative movement vector of the object with respect to the host vehicle can be calculated with high accuracy based on these. . Further, when calculating the relative movement vector of the object, the object position information of a plurality of places recognized at a certain time interval is required. Conventionally, an object position is calculated from left end lateral position information, right end lateral position information, and distance information, and a relative movement vector of the object is obtained by recognizing a plurality of positions at a certain time interval. On the other hand, if the relative movement vectors of the left end and the right end are individually calculated as in the vehicle periphery monitoring device described above, the amount of calculation for obtaining the same accuracy can be increased as compared with the conventional method. Can be reduced. For example, a method of calculating the relative position vector by recognizing ten object positions and a method of calculating the relative movement vector by recognizing the left end position and the right end position of the object five by five can obtain the same accuracy. The latter method requires about half the amount of calculation compared to the former method. Further, in the latter method, if the left end position and the right end position are recognized 10 positions and the relative movement vectors are calculated, the calculation accuracy can be doubled with the same amount of calculation as the former method.

  According to the present invention, in the vehicle periphery monitoring device provided with the image detection means, it is possible to improve the calculation accuracy of the relative movement vector of the object with respect to the host vehicle.

  DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments of a vehicle periphery monitoring device according to the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and redundant description is omitted.

  First, the configuration of the vehicle periphery monitoring device 1 will be described with reference to FIG. FIG. 1 is a diagram showing a configuration of a vehicle periphery monitoring device 1 according to the present embodiment.

  The vehicle periphery monitoring device 1 is a device that is mounted on an automobile, detects an object such as a preceding vehicle that travels in front of the host vehicle, and calculates a relative movement vector of the object with respect to the host vehicle. The vehicle periphery monitoring device 1 provides each piece of information related to the calculated relative movement vector to a driving support device such as a collision prevention device, an inter-vehicle distance control device, and a follow-up traveling device that require information about a forward object. The vehicle periphery monitoring device 1 includes a millimeter wave radar 2, a stereo camera 3, and an electronic control device (hereinafter referred to as “ECU”) 4. In addition, the vehicle periphery monitoring device 1 may be configured separately from the above-described driving support device, and may transmit the calculated information to the driving support device, or may be configured to be incorporated in the driving support device.

  In the present embodiment, the millimeter wave radar 2 corresponds to the radar detection means described in the claims, the stereo camera 3 corresponds to the image detection means described in the claims, and the ECU 4 corresponds to the claims. This corresponds to the calculation means described.

  The millimeter wave radar 2 is a radar that detects a forward object using millimeter waves (transmission waves). The millimeter wave radar 2 is attached to the center of the front surface of the automobile. The millimeter wave radar 2 transmits the millimeter wave forward from the host vehicle and receives the millimeter wave reflected on the object surface. Then, the millimeter wave radar 2 generates information (distance information) related to the distance from the front end of the host vehicle to the object surface by measuring the time from transmission to reception. Further, the millimeter wave radar 2 is provided with a plurality of receiving units side by side. The millimeter wave radar 2 generates information (lateral position information) on the lateral position of the object with respect to the host vehicle based on the mutual time difference that occurs when each receiving unit receives the millimeter wave. Here, the lateral position of the object is the distance between the center line in the vehicle width direction of the host vehicle and the center line in the same direction of the object (both virtual lines). The millimeter wave radar 2 is connected to the ECU 4 and provides the generated distance information and lateral position information to the ECU 4. In the present embodiment, the millimeter wave radar 2 generates distance information and lateral position information. However, the ECU 4 and other ECUs generate such information based on signals provided from the millimeter wave radar 2. It is good.

  The stereo camera 3 is composed of two CCD cameras (not shown), and the two CCD cameras are arranged at a distance of about several centimeters in the horizontal direction. The stereo camera 3 is also attached to the center of the front surface of the host vehicle. The stereo camera 3 transmits image data captured by the two CCD cameras to an image processing unit (not shown). This image processing unit may be provided integrally with the stereo camera 3, or may be configured in the ECU 4 or another ECU.

  The image processing unit identifies a forward object based on each image data and the lateral position information from the millimeter wave radar 2, and generates information regarding the left end lateral position and the right end lateral position of the object. The image processing unit determines that a portion where the change in shading of the image data is significant is an end portion of the object, and generates information on the horizontal positions of the left and right ends, that is, left end lateral position information and right end lateral position information. The image processing unit is connected to the ECU 4 and provides the generated left end lateral position information and right end lateral position information to the ECU 4.

  The ECU 4 includes a microprocessor that performs calculations, a ROM that stores a program for causing the microprocessor to execute each process, a RAM that stores various data such as calculation results, and a backup RAM in which the stored contents are held by a 12V battery. It is comprised by. The ECU 4 calculates the relative position of the object with respect to the host vehicle based on the distance information to the object acquired from the millimeter wave radar 2 and the left end lateral position information and right end lateral position information of the object acquired from the stereo camera 3. Further, the ECU 4 calculates the relative movement vector of the object with respect to the host vehicle based on the difference between the current relative position and the relative position calculated in the past.

  Here, the generation of the left end lateral position information and the right end lateral position information by the stereo camera 3 has the following characteristics. When the angle between the direction of the position specifying object viewed from the stereo camera 3 and the imaging center axis of the stereo camera 3 is relatively small, that is, when the position specifying object in the image is close to the image center, the resolution is high and the accuracy is high. Position information can be generated. On the other hand, when the angle formed by the direction of the position specifying target viewed from the stereo camera 3 and the imaging center axis of the stereo camera 3 is large, that is, when the position specifying target in the image is close to the edge of the image, the resolution Becomes lower and the accuracy of the position information decreases.

More specifically, as shown in FIG. 2, an angle θ _L formed between the direction of the left end BL and right end BR of the forward vehicle B (corresponding to an object) viewed from the stereo camera 3 and the imaging center axis Ca of the stereo camera 3. , theta when _R is relatively small, as shown in FIG. 4 (a), left BL and right BR in the image D is close to the image center. In such a case, position information regarding the left end BL and the right end BR can be obtained with high accuracy. On the other hand, as shown in FIG. 3, when the lateral position of the forward vehicle B is separated from the center line in the vehicle width direction of the host vehicle A to the right, the direction of the right end BR of the forward vehicle B viewed from the stereo camera 3 and the stereo camera The angle θ _R formed with the imaging center axis Ca of 3 increases, and the right end BR in the image D is close to the end of the image as shown in FIG. In such a case, the accuracy of the position information regarding the right end BR decreases.

  Therefore, the vehicle periphery monitoring apparatus 1 according to the present embodiment calculates the relative movement vector of the object with respect to the host vehicle while considering the accuracy of the left end lateral position information and the right end lateral position information. Hereinafter, the operation of the vehicle periphery monitoring device 1 will be described with reference to FIG. FIG. 5 is a flowchart showing a procedure for calculating the relative movement vector between the host vehicle and the object by the vehicle periphery monitoring apparatus 1. This process is repeatedly executed at a predetermined timing in the ECU 4 from when the power source of the ECU 4 is turned on until it is turned off.

  First, the ECU 4 acquires the distance information from the own vehicle to the object and the lateral position information of the object with respect to the own vehicle generated in the millimeter wave radar 2 (step S1). Subsequently, the ECU 4 acquires information regarding the left end lateral position Xl and the right end lateral position Xr of the object generated in the stereo camera 3 (step S2).

  Next, the ECU 4 selectively performs one of the following two processes (weighting calculation process and left and right individual calculation process) according to the lateral position of the object. Note that the lateral position of the object used for determining which of these processes is to be performed may be the lateral position information generated by the millimeter wave radar in step S1, or the left end lateral position X1 and the right end in the previous calculation. It may be calculated based on the lateral position Xr.

[Weighting calculation processing]
When the lateral position of the object is not within a predetermined range from the center line of the host vehicle (for example, when the lateral position of the forward vehicle B is away from the center line in the vehicle width direction of the host vehicle A as shown in FIG. ), The ECU 4 performs the following processing. The ECU 4 calculates the lateral position X of the object by weighting each of the left end lateral position Xl and the right end lateral position Xr. That is, the ECU 4 multiplies the left end lateral position Xl by a weighting coefficient α (first weighting coefficient) that determines the weight of the left end lateral position information and the right end lateral position information. By adding a value (second value) βXr obtained by multiplying the right end lateral position Xr by a weighting coefficient β (second weighting coefficient, α + β = 1) that determines weighting, the lateral position X (= αXl + βXr) is calculated (step S3).

  Here, the above-described weighting coefficients α and β are set according to the lateral position of the object. That is, when the left end lateral position Xl is closer to the image center than the right end lateral position Xr, the weighting coefficient α is set larger than the weighting coefficient β, and the right end lateral position Xr is closer to the image center than the left end lateral position Xl. Is made larger than the weighting coefficient α. Information on the weighting coefficients α and β (weighting coefficient map) is stored in the ECU 4, and when the ECU 4 acquires the left end lateral position Xl and the right end lateral position Xr, the weighting coefficient is set by referring to the weighting coefficient map. The

  An example of the weighting coefficient map relating to the weighting coefficient α is shown in FIG. 6A, and an example of the weighting coefficient map relating to the weighting coefficient β is shown in FIG. As described above, when the position specifying target in the image is close to the center of the image, the stereo camera 3 can generate accurate position information because the resolution is high, but the position specifying target in the image is at the end of the image. In the case of being close, the resolution is lowered and the accuracy of the position information is lowered. Therefore, the weighting coefficient map regarding the weighting coefficients α and β is determined such that the weighting coefficient α increases and the weighting coefficient β decreases as the lateral position of the object is biased to the left. Conversely, it is determined that the weighting coefficient β increases and the weighting coefficient α decreases as the lateral position of the object deviates to the right. When the lateral position of the object is zero, that is, when the object is positioned in front of the host vehicle (stereo camera 3), the weighting coefficients α and β are determined to be equal.

  After calculating the lateral position X of the object as described above, the ECU 4 recognizes the relative position of the object with respect to the host vehicle based on the lateral position X and the distance information obtained in step S1. Then, the ECU 4 calculates a relative movement vector of the object with respect to the host vehicle based on a plurality of (for example, ten) relative positions sequentially recognized at a certain time interval (step S4).

[Right and left individual calculation processing]
When the lateral position of the object is within a predetermined range from the center line of the host vehicle (for example, when the lateral position of the front vehicle B is close to the center line in the vehicle width direction of the host vehicle A as shown in FIG. 2) The ECU 4 performs the following processing. In this case, the ECU 4 does not perform weighting such as [weighting calculation processing], and separately calculates the relative movement vector of the left end of the object with respect to the own vehicle and the relative movement vector of the right end of the object with respect to the own vehicle. Based on the relative movement vector, a relative movement vector of the object with respect to the host vehicle is calculated.

  Specifically, the ECU 4 recognizes the left end position of the object viewed from the host vehicle based on the left end lateral position X1 obtained in step S2 and the distance information obtained in step S1. Then, a relative movement vector regarding the left end of the object is calculated based on a plurality (for example, five) left end positions sequentially recognized at a certain time interval (step S5). The ECU 4 also performs the same calculation for the right end of the object, and calculates a relative movement vector for the right end (step S5). The ECU 4 calculates the relative movement vector of the object with respect to the host vehicle by averaging the relative movement vectors of the left end and the right end thus calculated (step S6).

  In the vehicle periphery monitoring apparatus 1 according to the present embodiment described above, the ECU 4 calculates the relative movement vector of the object with respect to the host vehicle by weighting each of the left end lateral position Xl and the right end lateral position Xr, At this time, the weight on the side closer to the center of the image in the left end lateral position Xl and the right end lateral position Xr is set larger than that on the far side. As described above, the position information on the side closer to the center of the image is more accurate than the position information on the far side, so by increasing the weight of the position information on the side closer to the center of the image than on the far side, The relative movement vector of the object with respect to the vehicle can be calculated with high accuracy.

  Further, as in the present embodiment, the ECU 4 does not perform such weighting when the lateral position of the object is within a predetermined range from the center line of the host vehicle, and calculates the relative movement vectors at the left end and the right end of the object. It is preferable to calculate each separately and calculate the relative movement vector of the object with respect to the host vehicle based on these relative movement vectors. As described above, when the lateral position of the object is close to the center line of the host vehicle, it can be said that the accuracy of both the left end lateral position Xl and the right end lateral position Xr is high. Therefore, in such a case, the relative movement vectors of the left end and the right end can be calculated with high accuracy, and the relative movement vector of the object with respect to the host vehicle can be calculated with high accuracy based on these relative movement vectors. Further, when calculating the relative movement vector, position information of a plurality of locations recognized at a certain time interval is required. Conventionally, the object position is calculated from the left end lateral position Xl, the right end lateral position Xr, and the distance information, and the relative movement vector of the object is obtained by recognizing a plurality of the object positions at a certain time interval. If the relative movement vectors at the left end and the right end are individually calculated as in the present embodiment, the amount of calculation for obtaining the same accuracy can be reduced as compared with such a conventional method. For example, as shown in FIG. 7 (a), 10 positions of the object position P1 are recognized to calculate the relative position vector V1 of the object (front vehicle B), and the left end position of the object as shown in FIG. 7 (b). In the method of calculating the relative movement vectors V2 and V3 by recognizing P2 and the right end position P3 for each of the five positions, the calculation accuracy is equal to each other, and the latter method has about half the calculation amount as compared with the former method. It becomes. Further, in the latter method, if the left end position and the right end position are recognized 10 positions and the relative movement vectors are calculated, the calculation accuracy can be doubled with the same amount of calculation as the former method.

  The present invention is not limited to the above-described embodiments. For example, in the above embodiment, millimeter wave radar is used as the radar detection means, but any type of radar may be used. Further, although a stereo camera is used as the image detection means, any type of camera may be used.

It is a figure which shows the structure of the vehicle periphery monitoring apparatus which concerns on this Embodiment. The case where the angle which the direction of the left end of the front vehicle seen from a stereo camera and the right end direction and the imaging center axis line of a stereo camera make is comparatively small is shown. The case where the angle which the direction of the right end of the front vehicle seen from the stereo camera and the imaging center axis line of a stereo camera make is large is shown. (A) The case where the left end and the right end of the object in the image are close to the center of the image is shown. (B) The case where the right end of the object in the image is close to the end of the image is shown. It is a flowchart which shows the calculation procedure of the relative movement vector of the own vehicle and an object by a vehicle periphery monitoring apparatus. (A) An example of the weighting coefficient map regarding the weighting coefficient α is shown. (B) shows an example of a weighting coefficient map related to the weighting coefficient β. (A) The state which recognizes ten object positions and calculates the relative position vector of an object (front vehicle) is shown notionally. (B) It shows conceptually how the relative movement vector is calculated by recognizing the left end position and the right end position of the object five by five.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Vehicle periphery monitoring apparatus, 2 ... Millimeter wave radar, 3 ... Stereo camera, A ... Own vehicle, B ... Front vehicle, BL ... Left end, BR ... Right end, Ca ... Imaging center axis, D ... Image.

Claims (3)

A vehicle periphery monitoring device for detecting a relative movement direction and a relative movement speed of an object with respect to the own vehicle,
Radar detection means for generating distance information and lateral position information of the object relative to the host vehicle by transmitting a transmission wave and receiving a reflected wave reflected by the object;
Image detection means for generating left end lateral position information and right end lateral position information of the object based on the image obtained by imaging the object and the lateral position information;
Calculation means for calculating a relative movement direction and a relative movement speed of the object with respect to the host vehicle based on the distance information, the left end lateral position information, and the right end lateral position information;
The calculating means weights each of the left end lateral position information and the right end lateral position information to calculate a relative moving direction and a relative moving speed of the object with respect to the host vehicle, and at the time of the weighting, A vehicle periphery monitoring device, wherein the weight of the position information closer to the center of the image of the lateral position information and the right end lateral position information is made larger than that of the far side. The computing means adds a first value obtained by multiplying the left end lateral position information by a first weighting factor and a second value obtained by multiplying the right end lateral position information by a second weighting factor. Calculating the relative position of the object with respect to the host vehicle, and calculating the relative movement direction and the relative movement speed of the object with respect to the host vehicle based on the relative position;
When the left end is closer to the center of the image than the right end of the object, the first weighting factor is made larger than the second weighting factor, and the right end is closer to the center of the image than the left end of the object. 2. The vehicle periphery monitoring apparatus according to claim 1, wherein the second weighting coefficient is made larger than the first weighting coefficient in some cases.   When the lateral position of the object is within a predetermined range from the center line of the host vehicle, the calculation means does not perform the weighting and performs a relative movement direction and a relative movement of the left end of the object with respect to the host vehicle. The speed, the relative movement direction and the relative movement speed of the right end of the object with respect to the own vehicle are respectively calculated, and the relative movement direction and the relative movement speed of the object with respect to the own vehicle are calculated based on the relative movement direction and the relative movement speed. The vehicle periphery monitoring device according to claim 1, wherein the vehicle periphery monitoring device is calculated.

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